Insights

Insights and practical notes from delivery across data engineering, analytics, BI, and governance

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FeaturedBI & Visualization8 min read

Why Most BI Projects Fail Before the First Dashboard

The fundamental reasons BI initiatives fail aren't technical—they're organizational. Here's what to address before building your first report.

BIStrategyProject ManagementChange Management
FeaturedAnalytics Engineering10 min read

Analytics Engineering Is Not Just dbt

dbt is a powerful tool, but analytics engineering is a discipline. Understanding the difference is crucial for building sustainable data practices.

Analytics EngineeringdbtData ModelingBest Practices
FeaturedAnalytics Engineering12 min read

KPI Standardization: From Definitions to Semantic Layers

Standardizing KPIs requires more than agreement—it requires infrastructure. Here's how semantic layers enable consistent metrics across your organization.

KPIsSemantic LayerAnalytics EngineeringData Modeling
BI & VisualizationNovember 15, 20248 min read

Why Most BI Projects Fail Before the First Dashboard

The fundamental reasons BI initiatives fail aren't technical—they're organizational. Here's what to address before building your first report.

BIStrategyProject ManagementChange Management
Analytics EngineeringOctober 20, 202410 min read

Analytics Engineering Is Not Just dbt

dbt is a powerful tool, but analytics engineering is a discipline. Understanding the difference is crucial for building sustainable data practices.

Analytics EngineeringdbtData ModelingBest Practices
Governance & QualitySeptember 18, 20249 min read

Data Quality Is a Product, Not a Script

Treating data quality as a technical checklist misses the point. Quality is a product feature that requires product thinking—design, iteration, and user focus.

Data QualityData GovernanceProduct ThinkingBest Practices
Analytics EngineeringAugust 22, 202412 min read

KPI Standardization: From Definitions to Semantic Layers

Standardizing KPIs requires more than agreement—it requires infrastructure. Here's how semantic layers enable consistent metrics across your organization.

KPIsSemantic LayerAnalytics EngineeringData Modeling
Data EngineeringJuly 10, 202411 min read

SQL Patterns I Use for Reliable ETL

Production-tested SQL patterns for building ETL pipelines that handle edge cases, maintain data quality, and fail gracefully.

SQLETLData EngineeringBest Practices

As Seen on Medium

Additional articles published on Medium covering data engineering, analytics, and industry insights.